Tuesday, December 6, 2016

Data Analytics with WSO2 Analytics Platform

Data Analytics and Visualization is a key requirement for any organization today. Proper Analytics and Visualization of data helps make better informed business decisions, reduce losses and increase profitability.

Data Analytics requirements can vary depending on what kind of data you need to analyze, the input mediums as well as the urgency of when it needs to be analyzed and acted upon.

Today any organization would produce a large amount of data. This data could be complex, scattered and transmitted through multiple mediums and protocols. Capturing this data and conducting analysis on large sets of structures and unstructured data could be a daunting task.

Furthermore, there are occasions where data needs to be analyzed as they are produced in real time.

In other cases it is required to predict future events or trends based on historical and current data.

And in all cases data visualization is a key aspect. Interactive dashboards would make it easy for users to interact with data using functions such as sort and filter and make the decision making process much easier. 

What WSO2 offers:

WSO2 offers a complete Analytics Platform that provides solutions for all the aforementioned use-cases. The WSO2 Analytics platform offers the following:

Batch Analytics
Analyze a set of data collected over a period of time.
Suitable for high volumes of data.

Real-Time Analytics
Continuous processing of input data in real time.
Suitable for critical systems where immediate actions is required e.g: Flight radar systems

Interactive Analytics
Obtaining fast results on indexed data by executing ad-hoc queries

Predictive Analytics
Predict future events by analyzing historical and current data

Batch Analytics

Lets look at Batch Analytics in the perspective of Big Data.

What is Big Data ?

“Big data is a term for data sets that are so large or complex that traditional data processing applications are inadequate to deal with them”    - (Ref: Wikipedia)

Why Analyze Big Data ?

  • Make informed Business decisions - make decisions based on patterns emerging from analyzing historic data
  • Improve customer experience - discover customer preferences, purchasing patterns and present the most relevant data
  • Process Improvements - identify areas of the business process that needs improvement 

Example: Better customer experience in airline seat reservation/allocation

Automatically allocate seats to customers based on their previous seat booking preferences by analyzing historic data related to seat reservations.


img ref: http://staticcontent.transat.com/airtransat/infovoyageurs/content/EN/seating-plan-a310-300(1).png

Real Time Analytics

Identify most meaningful events within an event cloud
Analyze the impact
Acts on them in real time

Example: City Transport Control System - Analyzing traffic, monitor movement of buses, generate alerts based on traffic, speed & route
img ref: http://wso2.com/library/demonstrations/2015/02/screencast-analyzing-transport-for-london-data-with-wso2-cep/

Predictive Analytics:

  1. Machine Learning
  2. Other approaches such as statistical modeling
Machine learning is the science of getting computers to act without being explicitly programmed - (ref: http://online.stanford.edu/)

Example: e-Commerce sites use predictive analytics to suggest the most relevant merchandize, increasing sales opportunity

img ref: Amazon.com